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CATEGORIES:
CONTACT:https://events.ecmwf.int/event/488/
DESCRIPTION:This ECMWF-ESA Machine Learning Workshop aims to explore the fu
sion of traditional Earth System Observation and Prediction (ESOP) techniq
ues with machine learning (ML) and deep learning (DL) methods.\nIt seeks t
o showcase the impact achieved through this fusion\, while also addressing
the remaining challenges that need further exploration. The presenters wi
ll show their contributions to this field and engage the attendees in disc
ussions to provide a comprehensive understanding of the subject. The works
hop strongly welcomes industry to demonstrate their commercial lenses for
ML4ESOP applications.\nThis event will delve into the transformative role
of ML in enhancing data analysis and predictive modelling within atmospher
ic sciences. Participants will engage with leading experts\, partake in ha
nds-on sessions\, and explore cutting-edge innovations that are shaping th
e future of climate research and operational forecasting.\nTickets: https:
//events.ecmwf.int/event/488/.
DTSTART;TZID=Australia/Sydney:20260413T090000
DTEND;TZID=Australia/Sydney:20260417T170000
LOCATION:Online event
SEQUENCE:0
SUMMARY:Machine Learning for Earth System Observation and Prediction
URL:https://www.spatialsource.com.au/event/machine-learning-for-earth-syste
m-observation-and-prediction/
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X-ALT-DESC;FMTTYPE=text/html:\\n\\n\\n\\n\\nThis ECMWF-ESA Machine Learning Workshop aims to e
xplore the fusion of traditional Earth System Observation and Prediction (
ESOP) techniques with machine learning (ML) and deep learning (DL) methods
.
\nIt seeks to showcase the impact achieved through this f
usion\, while also addressing the remaining challenges that need further e
xploration. The presenters will show their contributions to this field and
engage the attendees in discussions to provide a comprehensive understand
ing of the subject. The workshop strongly welcomes industry to demonstrate
their commercial lenses for ML4ESOP applications.
\nThis event will delve into the transformative role of ML in enhancing data analysi
s and predictive modelling within atmospheric sciences. Participants will
engage with leading experts\, partake in hands-on sessions\, and explore c
utting-edge innovations that are shaping the future of climate research an
d operational forecasting.
\nTickets: https://events.ecmwf.int
/event/488/.
X-TAGS;LANGUAGE=en-US:climate change\,deep learning\,Earth observation\,mac
hine learning
X-TICKETS-URL:https://events.ecmwf.int/event/488/
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